Everyone knows all the usual suspects for customer segmentation. Easily collectible demographics data such as age, gender, and location, are easy wins for companies looking to personalize their marketing materials. In the next few years, the tools that we use for segmentation will give companies an even more significant understanding of each customer on an individual level. Machine learning and automation are increasingly being used to improve data analysis. These tools will quickly become the norm for any digital business. Still, there are some common misconceptions about the best practices for segmentation.
In this blog, I’ll show you five factors to consider before you begin your segmenting your customers.
Customer Behavior is Just as Important as Customer Details
Effective segmentation digs deeply. It involves an analysis of customer behavior, not just quickly available data like customer details. What actions are customers taking once they hit your website? Do their actions resemble those of other customers? Does there seem to be a trend? Not many brands dive into segmentation as customer actions as thoroughly as they should. For example, many companies sort customers based on who abandons their cart on ecommerce sites. In these cases, companies might offer a discount or reach out to ask if they had any questions about the product.
But what if you segmented that group even further? Further segments could include those for customers who never entered their credit card information, customers whose credit card has been denied, or customers who failed to enter a single detail after adding a product to their cart. By tracking and sorting customers based on their behavior on your site, you can better inform your marketing materials and customize your messages for each customer type. You can then design your landing pages to target specific customer types. Landing page builders like Unbounce are helpful tools for this since they let you design your landing pages and other marketing materials according to your segmentation of customers.
Automation and Machine Learning are Inherent Parts of Effective Segmentation
A big reason so few brands haven’t used segmentation to its full potential is that sorting through all that data can be tedious. It can take days to sift through data by hand and properly adequately categorize each person to ensure your assessments are accurate. And accuracy is important here: you wouldn’t want to send out customer emails only to find that you have miscalculated or missed a data point.
Automation and machine learning have re-shaped digital marketing and segmentation in particular. An excellent engagement platform can provide hyper-targeting that examines the customer journey and then automatically optimizes your marketing materials for specific customer types, helping you interact with customers on a more personal level. These tools will become the standard for all brands doing serious business online, simply because of the added value they provide.
Micro-Segmentation Builds Trust
Customers love brands that understand them. That’s why it’s so important to speak to their pain points in every piece of marketing that you create. Customers want to know that companies understand their needs, pains, and desires. They also want to be assured that the product you offer will solve their relevant problems.
Micro-segmentation is about sorting your customers into more specific categories. In typical segmentation, you might have customer segments based on who lives in Denver, who has a job title of Vice President, or who is above the age of 50. An example of a micro-segment would be a segment that includes all three—50+-year-old VPs who live in Denver.
According to an Infosys survey, 78% of customers stated that they’re more likely to buy from a company that sends them more targeted offers. Building that initial trust is incredibly important—customers who have been buying from a company for 30 or more months spend 67% more per order than they did on their first purchase. Micro-segmentation helps you win that trust by allowing you to speak to customers’ most significant concerns.
Segmentation Research Should Inform Product Development
At its core, segmentation begins with learning more about your customers. After all, the more you know about your customers, the more you can tailor your marketing to their unique problems, preferences, and desires.
Segmentation data should go beyond marketing; it should also be used to inform product development. Startups often pivot to find a market that needs solutions, and proper segmentation can help them pinpoint the best market. While no established business is going to do a full-fledged pivot in the same way that a startup would, many could benefit from more customer data involvement in product development.
Since detailed customer data is one of the most powerful tools available to companies, companies should design a product based on data-informed facts, rather than on their own assumptions.
Customer Needs are Not Static
A big mistake that brands make during the segmentation process is to stop their analysis as soon as they place customers in their respective segments. These customers will forever remain in that segment—even if additional data is collected in the future.
The problem here is that customer needs and preferences change over time. Today’s customers might be in a completely different place in life than they had been a year prior. Continuously working to correctly categorize customer types will help you more accurately target customers in your marketing and sales strategy.
Personalization is the Future
In-depth segmentation of your audience gives you more opportunities for personalization. It allows you to gain a detailed analysis of each customer so that you can tailor your sales and marketing efforts accordingly. While segmentation itself isn’t a new concept in digital marketing, the tools that we have available are making micro-segmentation increasingly feasible for companies of all sizes.
Segmentation can make or break your business. As more companies move toward the possibility and potential of an audience segment of one, it is paramount to create segmentation that can scale. How have you utilized segmentation to improve your customer’s experience? What tips will you implement from the advice given in this blog? Let’s keep the conversation going in the comments.
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